suffering.social
Current model total $2,355,067,000,000
Lives lost$122.1B Depression$1.9T Economic loss$315.0B
Subconscious.ai

An open model | United States | 2009 to today

What might social media have cost us?

Lives cut short, years with depression, medical bills, and missed work.

The comparison is a United States where social media did not expand beyond its 2009 reach. We cannot observe that other world. The total changes when you change the assumptions.

Review the assumptions or start with a preset.

Estimated cost if these assumptions are true $2,355,067,000,000 Review every assumption

This setting includes about 8,910 deaths and 30 million years lived with depression.

How the total is built

Observed change×Share caused by social media×Public value

Research measures parts of the observed change. You choose the uncertain share. Public guidance and cost studies convert the result into dollars.

Model inputs

What the total depends on

Move any slider. The sensitivity range shows how much that choice can change the total.

Each normal curve is a visual guide to the model range. It does not show the probability of any value.

Choose a study when its finding measures this input. Adjust the value to test a different assumption. Watch the estimate and formula change together.

Lives lost

Estimates the public cost of deaths that happened earlier than expected.

49K × 18% × $13.7M = $122B

A standard number used by public agencies. It is not the price of a person.

$13.7M
$13.7M
$7M lowSensitivity range$14M high

Model range $7M to $14M ·

Change in deaths represented in the mortality component.

49.5K
49.5K
30K lowSensitivity range70K high

Model range 30K to 70K deaths ·

This is a working estimate. No study measured this share directly.

18%
18%
7% lowSensitivity range30% high

Model range 7% to 30% ·

Mental health

Estimates the cost of years lived with depression.

5.0M × 6 years × 35% × $183K = $1.9T

The number of people included in this estimate.

5.0M
5.0M
2M lowSensitivity range8M high

Model range 2M to 8M ·

The average number of years each person is affected.

6.0 years
6.0 years
3 years lowSensitivity range8 years high

Model range 3 to 8 years ·

The average loss during each affected year.

35%
35%
30% lowSensitivity range50% high

Model range 30% to 50% ·

Economic effects

Counts direct care and lost productivity over time.

5.0M × ($8K + $6K) × 4.5 years = $315B

Extra spending on treatment and care.

$8K
$8K
$6.5K lowSensitivity range$12K high

Model range $6.5K to $12K ·

Lost income from missed work and reduced hours.

$6K
$6K
$4K lowSensitivity range$10K high

Model range $4K to $10K ·

Years in which care and productivity effects are counted.

4.5 years
4.5 years
0.25 years lowSensitivity range6.8 years high

Model range 0.25 to 6.8 years ·

Current result

$2.4T if the current assumptions are true

This model output compares assumptions. No one measured this loss, and it does not describe one person's experience.

Method & sources

See how the estimate works

The calculator adds the cost of lives lost, years lived with depression, healthcare, and missed work. You can change every part.

Limitations

What this estimate cannot tell us

  • A study can find a link without proving the same cause for every person.
  • We cannot directly observe what would have happened without social media.
  • Costs overlap, vary across populations, and should not be interpreted as a clinical diagnosis.

Evidence index

What this calculator can support

The output is an illustrative cumulative estimate for the United States since 2009. It combines editable assumptions about lives lost, years with depression, healthcare spending, and missed work.

A source's reported finding sets an input only when it measures the same quantity. Other sources provide context. Open any source to check the difference.

  • Government valuationEvidence role: agency guidance | Model mapping: direct central estimate
  • National trend estimateEvidence role: national surveillance | Model mapping: does not set this input
  • Exposure studyEvidence role: rollout comparison | Model mapping: context only; different population and outcome
  • Population estimateEvidence role: longitudinal study | Model mapping: does not set this input
  • Disease burdenEvidence role: global burden estimate | Model mapping: does not set this input
  • Health utilityEvidence role: quality-of-life study | Model mapping: lower end of the reported range
  • Care costEvidence role: economic estimate | Model mapping: reported value rounded to the slider step
  • Work lossEvidence role: workplace burden study | Model mapping: midpoint of the reported per-person range
  • Duration estimateEvidence role: treatment duration study | Model mapping: reported average

What surveys show

What changed around 2012?

Around 2012, more teenagers began reporting serious sadness and other mental health problems. Smartphones and social media also became a bigger part of daily life.

These changes happened at about the same time. That does not prove that one caused the other. Researchers need careful comparisons to test possible causes.

Illustrative index of adolescent mental-health distress, 2005 to 2021 The survey number stays fairly steady through 2011 and rises after 2012. The dashed line asks what might have happened without the change. Researchers did not measure that line. Observed turn Observed pattern Unobserved world 2005 2012 2021
The solid line shows the pattern seen in national surveys. The dashed line asks what might have happened without the change. Researchers did not measure that line.

Researchers use several checks to study the change.

  1. Check more than one survey.

    A real change should appear in several trusted sources. One chart is not enough.

  2. Compare similar groups.

    Researchers compare people who got access earlier with similar people who got access later.

  3. Test every guess.

    Change each assumption and see how much the final estimate moves.

Primary evidence

  • SAMHSA · National Survey on Drug Use and Health · 2004 to 2021
  • CDC · Youth Risk Behavior Surveillance System
  • Braghieri, Levy & Makarin · American Economic Review · 2022
  • Allcott et al. · American Economic Review · 2020

This calculator does not give a final verdict. It shows the choices behind the estimate so you can test them yourself.

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